<h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">SENIOR PRODUCT MANAGER - TECH, EXPERIMENTATION &amp; FAILURE</strong></span></h4><hr><p><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">COMPANY:</strong></span><a target="_blank" href="http://Steven.com"><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2"> STEVEN.
COM</strong></span></a></p><p><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">REPORTING TO: </strong></span><a target="_blank" href="https://www.linkedin.com/in/adapema/"><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">CITO</strong></span></a></p><p><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">LOCATION: </strong>LONDON</span></p><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">ABOUT</strong></span><a target="_blank" href="http://steven.com"><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2"> </strong></span></a><a target="_blank" href="http://STEVEN.
COM"><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">STEVEN.
COM</strong></span></a></h4><p><a target="_blank" href="http://Steven.com"><span>Steven.com</span></a><span> is building the operating system for the creator economy, forecast to pass a trillion dollars by the early 2030's. This industry is currently held back by fragmented tools and a lack of professional infrastructure.</span><a target="_blank" href="http://steven.com/"><span> </span></a><a target="_blank" href="http://Steven.com"><span>Steven.com</span></a><span> is the unlock. We are the end-to-end Operating System designed to scale what is irreplaceably human.</span></p><p><span>We have built proprietary technology and obsessed teams to identify and scale the highest-potential creators across our core pillars:</span></p><ul><li><p><span>Creator Media: Amplifying reach, influence, and trust</span></p></li><li><p><span>Creator Community: Transforming audiences into connected tribes</span></p></li><li><p><span>Creator Products: Providing creators with the infrastructure to build and back aligned products and ventures</span></p></li><li><p><span>Powered by Creator Tech &amp; Intelligence: A proprietary data and technology suite that fuels smarter decisions and drives innovation across the entire flywheel.</span></p></li></ul><p><span>Our Experimentation &amp; Failure team has one of the most strategically important and unusual mandates at </span><a target="_blank" href="http://Steven.com"><span>Steven.com</span></a><span>: increase the rate of failure. As Steven Bartlett puts it: "the path to the correct answer is out-failing your competition." This isn't a growth team or an optimisation function. It's the team that exists to make sure we learn faster than anyone else.</span></p><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">ROLE MISSION</strong></span></h4><p><span>Lead the Experimentation &amp; Failure team, reporting to the CITO. You'll out-experiment and out-fail the competition - running high-velocity, rigorous experiments across every show, creator, piece of content, and commercial bet at </span><a target="_blank" href="http://Steven.com"><span>Steven.com</span></a><span>, while building a team and a culture that treats deliberate failure as the primary learning mechanism. This is deeply hands-on: you'll be setting hypotheses, isolating variables, checking statistical power, reading results, and moving to the next test - not directing from a distance.</span></p><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">KEY OUTCOMES</strong></span></h4><ul><li><p><span>Own and drive the experimentation agenda across every show, creator, and IP property in the FlightStory portfolio - from podcast topic selection and episode structure through to thumbnail design and social tile copy. No detail too small to test.</span></p></li><li><p><span>Lead hypothesis formation for every experiment, with clear success, failure, and inconclusive criteria defined in advance - and enforce single-variable discipline across the board.</span></p></li><li><p><span>Ensure every experiment is adequately powered before launch: sample sizes calculated, measurement windows defined, results interpretable by design.</span></p></li><li><p><span>Systematically increase experimentation velocity and build the intake process that makes high-volume testing the default across FlightStory and </span><a target="_blank" href="http://Steven.com"><span>Steven.com</span></a><span>.</span></p></li><li><p><span>Build institutional memory - a searchable, structured record of every experiment run, what was learned, and what was decided - as a compounding organisational asset.</span></p></li><li><p><span>Partner with the VP of Engineering &amp; Applied AI to apply AI tooling to experiment design, analysis, and reporting, and to ensure infrastructure supports testing at this velocity.</span></p></li></ul><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">CORE COMPETENCIES</strong></span></h4><ul><li><p><span>Deep, first-principles command of experimentation mathematics: statistical significance, power, sample size calculation, p-values, confidence intervals, Type I/II errors, and the difference between statistical and practical significance.</span></p></li><li><p><span>Genuine mastery of the scientific method applied to product and content - hypothesis formation, single-variable isolation, measurement design, and result interpretation.</span></p></li><li><p><span>A track record of building experimentation culture, not just running tests - creating an environment where the whole team experiments and failure is rewarded.</span></p></li><li><p><span>Comfortable querying data and working shoulder-to-shoulder with engineers and data scientists at implementation depth.</span></p></li><li><p><span>Strong written and verbal communication - able to write a hypothesis an engineer respects and explain a result a producer will act on.</span></p></li><li><p><span>Experience operating at pace, in high-volume testing environments where speed of learning is the competitive edge.</span></p></li></ul><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">YOU'LL THRIVE HERE IF</strong></span></h4><ul><li><p><span>You think in hypotheses, not features.</span></p></li><li><p><span>You isolate one variable at a time, and understand viscerally why changing five things at once makes a result meaningless.</span></p></li><li><p><span>You give a null or inconclusive result the same intellectual respect as a win - you know how to extract the signal either way.</span></p></li><li><p><span>You're obsessive about measurement: an experiment that can't be measured is just a change, not an experiment.</span></p></li><li><p><span>You're deeply sceptical of your own results, and design experiments to prove yourself wrong rather than confirm what you already believe.</span></p></li><li><p><span>You move fast, expect others to move fast, and don't wait for perfect conditions to run a test.</span></p></li><li><p><span>You believe failure is feedback, feedback is knowledge, and knowledge is power - and you build systems to generate that knowledge at the highest possible rate.</span></p></li></ul><hr><h4><span><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2">IDEAL BACKGROUND</strong></span></h4><ul><li><p><span>Demonstrable experience leading (not just participating in) product or content experimentation programs at a technology, media, or creator-economy company - owning the methodology, volume, and culture.</span></p></li><li><p><span>Strong advantage: experience with algorithmic platforms and how to design experiments against platform-specific metrics; podcasting, video, social, or creator-economy background; familiarity with YouTube/Spotify/social analytics (CTR, retention, watch time, audience behaviour).</span></p></li><li><p><span>Nice to have: experience building an experimentation platform from scratch; familiarity with causal inference beyond standard A/B testing (holdouts, quasi-experiments, diff-in-diff); experience experimenting on AI/ML systems or prompt variations in production; a background in statistics, maths, CS, economics, or a natural science; exposure to early-stage environments where you had to build the experimentation infrastructure yourself.</span></p></li></ul><hr><p><strong id="docs-internal-guid-d1407fc5-7fff-d6f7-65f2-f65da18d89f2"><br></strong></p>